World Library  

QR link for Complex Networks for Streamflow Dynamics : Volume 18, Issue 11 (20/11/2014)
Add to Book Shelf
Flag as Inappropriate
Email this Book

Complex Networks for Streamflow Dynamics : Volume 18, Issue 11 (20/11/2014)

By Sivakumar, B.

Click here to view

Book Id: WPLBN0004011280
Format Type: PDF Article :
File Size: Pages 14
Reproduction Date: 2015

Title: Complex Networks for Streamflow Dynamics : Volume 18, Issue 11 (20/11/2014)  
Author: Sivakumar, B.
Volume: Vol. 18, Issue 11
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2014
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Woldemeskel, F. M., & Sivakumar, B. (2014). Complex Networks for Streamflow Dynamics : Volume 18, Issue 11 (20/11/2014). Retrieved from http://cn.ebooklibrary.org/


Description
Description: School of Civil and Environmental Engineering, The University of New South Wales, Sydney, Australia. Streamflow modeling is an enormously challenging problem, due to the complex and nonlinear interactions between climate inputs and landscape characteristics over a wide range of spatial and temporal scales. A basic idea in streamflow studies is to establish connections that generally exist, but attempts to identify such connections are largely dictated by the problem at hand and the system components in place. While numerous approaches have been proposed in the literature, our understanding of these connections remains far from adequate. The present study introduces the theory of networks, in particular complex networks, to examine the connections in streamflow dynamics, with a particular focus on spatial connections. Monthly streamflow data observed over a period of 52 years from a large network of 639 monitoring stations in the contiguous US are studied. The connections in this streamflow network are examined primarily using the concept of clustering coefficient, which is a measure of local density and quantifies the network's tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels, which are based on correlations in streamflow data between the stations. The clustering coefficient values of the 639 stations are used to obtain important information about the connections in the network and their extent, similarity, and differences between stations/regions, and the influence of thresholds. The relationship of the clustering coefficient with the number of links/actual links in the network and the number of neighbors is also addressed. The results clearly indicate the usefulness of the network-based approach for examining connections in streamflow, with important implications for interpolation and extrapolation, classification of catchments, and predictions in ungaged basins.

Summary
Complex networks for streamflow dynamics

Excerpt
Beven, K. J.: Uncertainty and the detection of structural change in models of environmental systems, in: Environmental Foresight and Models: a Manifesto, edited by: Beck, M. B., Elsevier Science Ltd, Oxford, UK, 227–250, 2002.; Beven, K. J.: Benchmark papers in Streamflow Generation Processes, IAHS Press, Wallingford, UK, 2006.; Grayson, R. B. and Blöschl, G.: Spatial Patterns in Catchment Hydrology: Observations and Modeling, Cambridge University Press, Cambridge, UK, 2000.; Albert, R., Jeong, H., and Barabasi, A.-L.: Internet: Diameter of the world wide web, Nature, 401, 130–131, 1999.; Anderson, C. J.: Central Limit Theorem, the Corsini Encyclopedia of Psychology, John Wiley & Sons, Hoboken, NJ, USA, 2010.; Archfield, S. A. and Vogel, R. M.: Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments, Water Resour. Res., 46, W10513, doi:10.1029/2009WR008481, 2010.; Barabási, A.-L. and Albert, R.: Emergence of scaling in random networks, Science, 286, 509–512, 1999.; Berge, C.: The Theory of Graphs and Its Applications, Matheun, Ann Arbor, MI, USA, 1962.; Boers, N., Bookhagen, B., Marwan, N., Kurths, J., and Marengo, J.: Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System, Geophys. Res. Lett., 40, 4386–4392, doi:10.1002/grl.50681, 2013.; Bollobás, B.: Modern Graph Theory, Springer, New York, USA, 1998.; Bondy, J. A. and Murty, U. S. R.: Graph Theory with Applications, Elsevier Science Ltd, New York, USA, 1976.; Bouchaud, J.-P. and Mézard, M.: Wealth condensation in a simple model of economy, Physica A, 282, 536–540, 2000.; Cayley, A.: On the theory of the analytical forms called trees, Philos. Mag., 13, 172–176, 1857.; Dalin, C., Konar, M., Hanasaki, N., Rinaldo, A., and Rodriguez-Iturbe, I.: Evolution of the global virtual water trade network, P. Natl. Acad. Sci. USA, 109, 5989–5994, 2012.; Davis, K. F., D'Odorico, P., Laio, F., and Ridolfi, L.: Global spatio-temporal patterns in human migration: A complex network perspective, PLoS ONE, 8, e53723, doi:10.1371/journal.pone.0053723, 2013.; Duan, Q., Gupta, H. V., Sorooshian, S., Rousseau, A. N., and Turcotte, R.: Calibration of Watershed Models, in: Water Science and Application Series, vol. 6, American Geophysical Union, Washington, D.C., USA, 2003.; Erdös, P. and Rényi, A.: On the evolution of random graphs, Publ. Math. Inst. Hung. Acad. Sci., 5, 17–61, 1960.; Euler, L.: Solutio problematis ad geometriam situs pertinentis, Comment. Acad. Sci. Petropolitanae, 8, 128–140, 1741.; Freeman, L. C.: Centrality in social networks: conceptual clarification, Social Netw., 1, 215–239, 1978/79.; Girvan, M. and Newman, M. E. J.: Community structure in social and biological networks, P. Natl. Acad. Sci. USA, 99, 7821–7826, 2002.; Gupta, V. K., Rodriguez-Iturbe, I., and Wood, E. F.: Scale Problems in Hydrology: Runoff Generation and Basin Response, Water Science and Technology Library Series, Springer, Dordrecht, the Netherlands, 1986.; Hrachowitz, M., Savenije, H. H. G., Blöschl, G., McDonnell, J. J., Sivapalan, M., Pomeroy, J. W., Arheimer, B., Blume, T., Clark, M. P., Ehret, U., Fenicia, F., Freer, J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut, R. W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P. A., Uhlenbrook, S., Wagener, T., Winsemius, H. C., Woods, R. A., Zehe, E., and Cudennec, C.: A decade of predictions in ungaged basins (PUB) – a review, Hydrolog. Sci. J., 58, 1198–1255, 2013.; Kahya, E. and Dracup, J. A.: U.S. streamflow patterns in relation to the El Niño/Southern Oscillation, Water Resour. Res., 29, 2491–2503, 1993.; Kiang, J. E., Stewart, D. W., Archfield, S. A., Osborne, E. B., and Eng., K.: A national streamflow network gap analysis, US Geological Survey Scienti

 
 



Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.